mikaelsouza

print("Hello World!") 

mikaelsouza

Testando

mikaelsouza

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mikaelsouza

type term = Var of string | Lam of string * term | App of term * term
type value = Closure of ((string * value) list * string * term)

let rec eval env term =
  match term with
  | Var var -> List.assoc var env
  | Lam (param, body) -> Closure (env, param, body)
  | App (lambda, argument) -> (
      let lambda = eval env lambda in
      let argument = eval env argument in

mikaelsouza

import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim

MAX_SIZE = 3
device = torch.device('cpu')

# generating vocab
sentences = [

mikaelsouza

class HashMap(object):
    def __init__(self, bucket_size=10):
        self.bucket_size = bucket_size
        self.buckets = [None] * self.bucket_size

    def insert(self, key, value):
        hashed_key = hash(key)
        bucket_index = hashed_key % self.bucket_size
        self.buckets[bucket_index] = value

mikaelsouza

import warnings
import math
from functools import reduce
import collections
from collections import defaultdict
import numpy as np
from keras.datasets import mnist
from sklearn.tree import DecisionTreeClassifier
from sklearn.preprocessing import KBinsDiscretizer
from math import log2

mikaelsouza

import numpy as np
import sklearn.datasets as datasets
from keras import layers, models, utils


def main():
    # Loading dataset
    boston_dataset = datasets.load_boston()

    # Defining inputs and outputs of the neural network